Machine Learning-Based Silent Entity Localization Using Molecular Diffusion

Kose, Oyku Deniz; Gursoy, Mustafa Can; Saraçlar, Murat; Pusane, Alí Emre; Tuǧcu, Tuna

doi:10.1109/lcomm.2020.2968319

Cited by 21 publications

(11 citation statements)

References 17 publications

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“…In recent years, research on TN-RN distance estimation methods in MCvD has attracted significant attention [13]- [20]. In [15], the authors proposed to use Single Spike Feedback Signals to estimate the signal attenuation strategy and a round trip time (the time for signal transmission of TN-RN-TN), which required complex duplex nanomachines.…”

Section: Introductionmentioning

confidence: 99%

“…Another kind of source location is related to eavesdropper localization, which uses received signals generated by the RN to estimate the eavesdropper's location [19], [20]. In [19], the authors considered that when there was only one eavesdropper in a one-dimensional environment, the location of the eavesdropper is determined according to the change in the number of molecules received by the RN.…”

Section: Introductionmentioning

confidence: 99%

“…In [19], the authors considered that when there was only one eavesdropper in a one-dimensional environment, the location of the eavesdropper is determined according to the change in the number of molecules received by the RN. This scheme has been improved in [20], where the authors built a deep neural network to detect eavesdroppers near the TN and the RN by comparing the difference in the number of molecules received above and below the RN.…”

Section: Introductionmentioning

confidence: 99%

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Levenberg-Marquardt Method Based Cooperative Source Localization in SIMO Molecular Communication via Diffusion Systems

Miao¹,

Zhang²,

Xu³

2022

Preprint

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Molecular communication underpins nano-scale communications in nanotechnology. The combination of multinanomachines to form nano-networks is one of the main enabling methods. Due to the importance of source localization in establishing nano-networks, this paper proposes a cooperative source localization method for Molecular Communication via Diffusion (MCvD) systems using multiple spherical absorption receivers. Since there is no exact mathematical expression of the channel impulse response for multiple absorbing receivers, we adopt an empirical expression and use Levenberg-Marquardt method to estimate the distance of the transmitter to each receiver, based on which the location of the transmitter is obtained using an iterative scheme where the initial point is obtained using a multi-point localization method. Particle based simulation is carried out to evaluate the performance of the proposed method. Simulation results show that the proposed method can accurately estimate the location of transmitter in short to medium communication ranges.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Levenberg-Marquardt Method Based Cooperative Source Localization in SIMO Molecular Communication via Diffusion Systems

Miao¹,

Zhang²,

Xu³

2022

Preprint

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“…These low rates might be acceptable for some applications where the information to be transmitted is limited and the design goals target low-complexity and low energy consumption. Several examples to these applications are one-shot DiMC or DiMC with very long symbol durations [6], [7], anomaly detection [8], [9], entity localization [10], [11], bio-sensing applications, etc. On the other hand, at both micro-and macro-scales, employing DiMC for digital communication links naturally elicits interest in increasing data rates.…”

Section: Introductionmentioning

confidence: 99%

Towards High Data-Rate Diffusive Molecular Communications: Performance Enhancement Strategies

Gursoy,

Nasiri-Kenari,

Mitra

2021

Preprint

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Diffusive molecular communications (DiMC) have recently gained attention as a candidate for nano-to microand macro-scale communications due to its simplicity and energy efficiency. As signal propagation is solely enabled by Brownian motion mechanics, DiMC faces severe inter-symbol interference (ISI), which limits reliable and high data-rate communications. Herein, recent literature on DiMC performance enhancement strategies is surveyed; key research directions are identified. Signaling design and associated design constraints are presented. Classical and novel transceiver designs are reviewed with an emphasis on methods for ISI mitigation and performancecomplexity tradeoffs. Key parameter estimation strategies such as synchronization and channel estimation are considered in conjunction with asynchronous and timing error robust receiver methods. Finally, source and channel coding in the context of DiMC is presented.

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“…Molecular communication (MC) is a nanotechnology that uses chemical molecules as the carriers of information [1].…”

Section: Introductionmentioning

confidence: 99%

Modulation and Signal Detection for Diffusive-Drift Molecular Communication with a Mobile Receiver

Liao

Jia

et al. 2021

Mobile Information Systems

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Molecular communication (MC), which allows nanomachines to communicate with each other by using chemical molecules, is considered to be a promising method for communications in liquid environment. Available works on MC mainly focus on modulation and signal detection schemes for MC systems with fixed nanomachines, i.e., fixed molecular communication (FMC) systems. However, the more complex systems with mobile nanomachines (i.e., mobile molecular communication (MMC) systems) have been largely unexplored. This paper considers a MMC system with a fixed transmitter and a mobile receiver communicating over diffusive-drift channels of a limited boundary. We first propose a new modulation scheme to address the issue of misalignment in the signal detection of MMC systems by adopting three types of molecules in the signal modulation and modulating the transmitted signals into blocks with equal length to avoid the transferring of a signal error in the current block on the signal detection in other blocks. We then propose a new signal detection scheme of the MMC systems by calculating the distance between the transmitter and the receiver based on a distance prediction method and detecting signals at the receiver based on the decided adaptive concentration threshold in each time interval. To verify the efficiency of our proposed scheme, we then conducted extensive simulations by the Monte Carlo simulation, and comparisons are also made among our proposed schemes, a well-known fixed threshold signal detection scheme, the CATD scheme, the PAD scheme, and a low complexity signal detection scheme for MMC systems in terms of the BER (bit error rate). Results show that our proposed schemes can outperform these schemes regarding the BER.

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Machine Learning-Based Silent Entity Localization Using Molecular Diffusion

Cited by 21 publications

References 17 publications

Levenberg-Marquardt Method Based Cooperative Source Localization in SIMO Molecular Communication via Diffusion Systems

Levenberg-Marquardt Method Based Cooperative Source Localization in SIMO Molecular Communication via Diffusion Systems

Towards High Data-Rate Diffusive Molecular Communications: Performance Enhancement Strategies

Modulation and Signal Detection for Diffusive-Drift Molecular Communication with a Mobile Receiver

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